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A Novel Hybrid Approach Based on Wavelet Transform and Fuzzy ARTMAP Networks for Predicting Wind Farm Power Production.

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Τίτλος: A Novel Hybrid Approach Based on Wavelet Transform and Fuzzy ARTMAP Networks for Predicting Wind Farm Power Production.
Συγγραφείς: Haque, Ashraf Ul1, Mandal, Paras2, Meng, Julian3, Srivastava, Anurag K.4, Tseng, Tzu-Liang2, Senjyu, Tomonobu5
Πηγή: IEEE Transactions on Industry Applications. Sep2013, Vol. 49 Issue 5, p2253-2261. 9p.
Θεματικοί όροι: *Wind power plants, *Power resources forecasting, *Algorithms, Wavelet transforms, Fuzzy control systems, Soft computing, Scientific communication
Περίληψη: This paper presents a novel hybrid intelligent algorithm based on the wavelet transform (WT) and fuzzy ARTMAP (FA) network for forecasting the power output of a wind farm utilizing meteorological information such as wind speed, wind direction, and temperature. The prediction capability of the proposed hybrid WT +FA model is demonstrated by an extensive comparison with a benchmark persistence method, other soft computing models, and hybrid models as well. The test results show a significant improvement in forecasting error through the application of a proposed hybrid WT +FA model. The proposed hybrid wind power forecasting strategy is applied to real-life data from Kent Hill wind farm located in New Brunswick, Canada. [ABSTRACT FROM AUTHOR]
Copyright of IEEE Transactions on Industry Applications is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A Novel Hybrid Approach Based on Wavelet Transform and Fuzzy ARTMAP Networks for Predicting Wind Farm Power Production.
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  Data: *<searchLink fieldCode="DE" term="%22Wind+power+plants%22">Wind power plants</searchLink><br />*<searchLink fieldCode="DE" term="%22Power+resources+forecasting%22">Power resources forecasting</searchLink><br />*<searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Wavelet+transforms%22">Wavelet transforms</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+control+systems%22">Fuzzy control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Soft+computing%22">Soft computing</searchLink><br /><searchLink fieldCode="DE" term="%22Scientific+communication%22">Scientific communication</searchLink>
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  Data: This paper presents a novel hybrid intelligent algorithm based on the wavelet transform (WT) and fuzzy ARTMAP (FA) network for forecasting the power output of a wind farm utilizing meteorological information such as wind speed, wind direction, and temperature. The prediction capability of the proposed hybrid WT +FA model is demonstrated by an extensive comparison with a benchmark persistence method, other soft computing models, and hybrid models as well. The test results show a significant improvement in forecasting error through the application of a proposed hybrid WT +FA model. The proposed hybrid wind power forecasting strategy is applied to real-life data from Kent Hill wind farm located in New Brunswick, Canada. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of IEEE Transactions on Industry Applications is the property of IEEE and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1109/TIA.2013.2262452
    Languages:
      – Code: eng
        Text: English
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      Pagination:
        PageCount: 9
        StartPage: 2253
    Subjects:
      – SubjectFull: Wind power plants
        Type: general
      – SubjectFull: Power resources forecasting
        Type: general
      – SubjectFull: Algorithms
        Type: general
      – SubjectFull: Wavelet transforms
        Type: general
      – SubjectFull: Fuzzy control systems
        Type: general
      – SubjectFull: Soft computing
        Type: general
      – SubjectFull: Scientific communication
        Type: general
    Titles:
      – TitleFull: A Novel Hybrid Approach Based on Wavelet Transform and Fuzzy ARTMAP Networks for Predicting Wind Farm Power Production.
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            NameFull: Haque, Ashraf Ul
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            NameFull: Srivastava, Anurag K.
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            NameFull: Tseng, Tzu-Liang
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              M: 09
              Text: Sep2013
              Type: published
              Y: 2013
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